We describe TINE, a new automatic evalua- tion metric for Machine Translation that aims at assessing segment-level adequacy. Lexical.
We describe TINE, a new automatic evalua-tion metric for Machine Translation that aims at assessing segment-level adequacy.
Feb 16, 2023 · This growth in MT research has entailed the development of accurate automatic evaluation metrics that allow us to track the performance of MT.
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Sep 25, 2024 · This article explores the different ways in which MT accuracy is evaluated, listing a range of metrics and approaches that are used to gauge quality.
Sep 26, 2017 · • Measuring time spent on producing translations. – baseline: translation from scratch. – post-editing machine translation. But: time consuming ...
Miguel Rios, Wilker Aziz, Lucia Specia: TINE: A Metric to Assess MT Adequacy. WMT@EMNLP 2011: 116-122. manage site settings. To protect your privacy, ...
Jul 22, 2020 · MT metrics' primary purpose is to assess the quality of MT models, and not translation as such. Therefore, despite their usefulness when it ...
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Apr 29, 2019 · Manual evaluation gives a better result in order to measure the quality of MT and to analyze errors within the system output: adequacy and ...
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Automatic Machine Translation (MT) evaluation metrics have traditionally been evaluated by the correlation of the scores they assign to MT output with human.
The most recent improvements in the performance of evaluation metrics is related to the use of machine learning techniques in order to combine a wide variety of ...
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